Alzheimer's disease and dementia: what's the difference?

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The innovation actually relies on a traditional method of screening for cognitive impairment, known as the clock-drawing test. Subjects are asked to draw a clock that shows the time to be 11.10, and then copy a pre-drawn clock showing the same time. The test demonstrates how people perform when it comes to verbal understanding, memory, and spatial knowledge, and is used to detect Parkinson's and Alzheimer's. The team behind the latest digital pen study wanted to find a way to automate the test -- not only to speed up diagnoses, but remove doctor subjectivity and potentially help drive earlier diagnoses by using more detailed data markers.

Using the Anoto Live Pen, which measures a ballpoint tip's position 80 times a second using an inbuilt camera, the team (from MIT's Computer Science and Artificial Intelligence Laboratory, Lahey Hospital and several other universities across the US) was able to collect data from 2,600 tests performed over nine years. The pen was used in all these tests, meaning an incredible amount of data was collected, from the user's precise movements to every small hesitation.

The team used this data to build specialised software and create the digital Clock Drawing Test (dCDT). They found it to be far more accurate at delivering a diagnosis than the analogue original, which relies on a doctor's subjective interpretation of the drawings. Part of this could be put down to the fact the dCDT takes in more than just the finished drawing -- it produced other markers that relied on the process of drawing the clock. For instance, the team found that those with memory impairments spend far more time thinking about the drawing before they put pen to paper, than those without the disorder. Those with Parkinson's also took far longer to draw clocks that were usually on the small side. These are two outcomes the ordinary CDT had never accounted for before. "We've improved the analysis so that it is automated and objective," MIT's Cynthia Rudin said on MIT News. "With the right equipment, you can get results wherever you want, quickly, and with higher accuracy."

The hope is the test will save on the man hours spent diagnosing, or potentially misdiagnosing, a disorder. This is of vital importance, considering the length of time it can take to diagnose neurological disorders such as Alzheimer's, taking in a whole raft of different tests and processes.

As the algorithms used in the dCDT continue to be trained on yet more data, the team also hopes it will be able to pick up on new markers they are discovering, faster -- such as hesitation and drawing technique -- to allow for even earlier diagnoses, based on thousands of test results carried out over the years. "While our models will require additional testing for validation, they offer the possibility of substantial improvement in detecting cognitive impairment earlier than currently possible, a development with considerable potential impact in practice," the team writes.